Field of the Invention
Exemplary embodiments of the present invention relate to a system and a method for detecting a region of interest about a tilted line capable of detecting, as a region of interest (ROI), a portion where a tilted line is present in a front image acquired by a front looking camera equipped in a vehicle.
Description of the Related Art
Generally, a lane departure warning system (LDWS) is a system which detects a lane while a vehicle is driving to issue a warning when the vehicle is out of the lane.
A detection of a driving lane profoundly affects safe driving, and as a result, the accurate detection of the driving lane has been made by using various types of sensors which estimate and determine the position of the lane. That is, various sensors like an image sensor, a radar or lidar sensor, etc., have been used alone or in a fused form to detect a lane or recognize objects in front of a vehicle.
A vision based system using the image sensor may extract a lot of information at low cost and may use the existing various vision processing algorithms.
The vision based lane detection system detects a lane using an approximation method which extracts feature information from an input image, applies parameteric model matching for lane detection, and applies an update algorithm such as a Kalman filter or particle filtering, a method which applies non-parameteric model matching based on transform such as hough transform (HT), or the like.
Meanwhile, to increase performance of the lane detection and increase possibility of commercialization, there is a need to develop an algorithm which may adaptively cope with various road conditions or lane forms such as corresponding to various lane patterns like solid line and dashed-line lanes and a lane configured of direction indicators, corresponding to a change in colors of a lane like white (W), yellow (Y), blue (B), or red (R), or the like, corresponding to various road forms like a straight line lane, a curved lane, or the like, and corresponding to different road environment like a road structure, weather, a shade of a tree or lightness variation, incomplete pavement of a road.
A study on the lane detection against all the lane patterns or the road conditions of the actual road as described above has been currently progressed, and thus restrictive functions have reached commercialization.
However, there is a problem in that it is difficult to implement a real-time processing system due to a lot of computations and generality is limited due to physical limits of lane and road conditions.
Further, the existing lane detection method performs the lane detection on all the images without considering the condition in which the lane is limited, even though the area in which the lane is present is limited to a predetermined range in the image acquired by the fixed camera Therefore, the existing lane detection method has a problem in that it takes much time to process the image information.